Dear Colleagues, The ASA Statistical Learning and Data Science Section is pleased to announce the November webinar, presented by Dr. Ryan Tibshirani on November 30, 2022.
Title: Delphi's Epidata Project: Opportunities and Challenges in Auxiliary Surveillance for Public Health in the United States
Speakers: Dr. Ryan Tibshirani, Department of Statistics, University of California, Berkeley
Date and Time: November 30, 2022, 1:00 to 2:30 pm Eastern Time
Registration Link: ASA SLDS Webinar Registration Link [eventbrite.com]
Abstract: In 2015, the Delphi group (based out of Carnegie Mellon University) launched a system called Epidata, which was recently greatly expanded in 2020 in an effort to support the U.S. COVID-19 pandemic response. Epidata is a collection of data repositories, each of which contains signals to help track and forecast pathogens of concern to public health. A key feature of Epidata is that it leverages auxiliary data streams, which operate outside of traditional public health reporting. This talk will describe the directions we seek to take Epidata in the near future, numerous opportunities that we believe Epidata presents, as well as challenges therein.Presenter: Ryan Tibshirani is a Professor of Statistics at the University of California, Berkeley. From 2011-2022 he was a Professor of Statistics and Machine Learning at Carnegie Mellon University. He did his Ph.D. in 2011 in Statistics at Stanford University, and his B.S. in 2007 in Mathematics also at Stanford University. His research interests lie broadly in statistics, machine learning, and optimization. A major applied focus is on tracking and forecasting epidemics (primarily seasonal flu & COVID), which he does as a Principal Investigator of the Delphi group. He is also an Amazon Scholar in AWS AI Labs. He has won various awards and honors, such as the Mortimer Spiegelman award in 2022, and an IMS Fellowship in 2022.